Wake Forest University Health Sciences
Winston-Salem, North Carolina, 27157, United States
Location status: Recruiting
Location contact
Deepak Palakshappa, MD, MSHP
CONTACT
Rebecca Stone, MPH
CONTACT
NCT Number: NCT06942598
Food insecurity affects up to 30% of pregnancies and leads to worse health in pregnant people and their children, including an increased risk of gestational diabetes, pre-term birth, and future cardiometabolic chronic conditions (e.g., type 2 diabetes and obesity). Interventions are being utilized to address food insecurity in clinical care settings, but patients differ in the support needed to reduce food insecurity and health systems have limited resources to invest in these interventions. Rather than a single intervention, adaptively allocating interventions could be a more effective, equitable, and efficient approach to improve food security; the objectives of this pilot study are to determine the feasibility of recruiting, retaining, and adaptively providing food insecurity interventions to pregnant patients in anticipation of a large, definitive trial in the future.
Interested in participating?
Request Info18 year and older
Female
Interventional
Not applicable
Winston-Salem, North Carolina, 27157, United States
Location status: Recruiting
Deepak Palakshappa, MD, MSHP
CONTACT
Rebecca Stone, MPH
CONTACT
The US is facing a maternal and infant health crisis. Each year in the US there are >700 maternal deaths and >60,000 life-threatening pregnancy events. Despite decreasing in other high-income countries, maternal mortality has increased in recent years in the US with a staggering 1210 maternal deaths in 2019. Importantly, maternal deaths in the US are now less likely to be due to direct complications of childbirth, and are increasingly due to endocrine (e.g. gestational diabetes (GDM)) or cardiovascular (e.g. pre-eclampsia) conditions directly related to obesity and other nutrition-related chronic diseases. One significant contributor to maternal mortality is food insecurity (FI), or the lack of consistent access to the food needed for a healthy life. In 2023, 13.5% of US households, (>40 million people), were food insecure. Households with young children have higher rates of FI. Also, up to 30% of pregnancies are impacted by FI. Pregnant and postpartum women are especially vulnerable to the impacts of FI as they have increased nutritional requirements for the growing fetus and while breastfeeding. FI has been associated with inadequate or excessive gestational weight gain, GDM, and pregnancy-induced hypertension. Excess retained weight after pregnancy has important health consequences including development of type 2 diabetes. GDM and gestational weight retention also confer higher risk of complications in subsequent pregnancies and future cardiovascular disease. Additionally, FI is associated with increased risk of preterm birth and infants being born low birth weight, affecting children's growth trajectories and future risk of developing obesity.
To address the high prevalence of FI and its impact on health, national healthcare organizations, including the Centers for Medicare and Medicaid (CMS) and The American College of Obstetricians and Gynecologists, have recommended that health systems address FI as a routine part of clinical care. The integration of interventions to address FI in different populations, particularly those with nutrition-related conditions, has been termed "Food is Medicine". CMS has been piloting Food is Medicine interventions as part of Medicaid reform in several states, including North Carolina. Three "Food is Medicine" interventions that are being studied and used by health systems and insurers include: 1) referring patients to government benefits intended to support nutrition or directly providing food through the use of 2) produce prescriptions and 3) medically-tailored meals. Despite the growing use of FI interventions in clinical care settings, a 2023 systematic review highlighted the need for more research on healthcare system-based interventions to reduce FI in pregnancy.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Participants randomized to this arm will receive $10 worth of produce delivered to their home weekly. Participants will receive a weekly delivery of produce for 3 months.
Medically tailored meals will be delivered weekly to participant's homes for 3 months. During the 3 months, participants will receive 10 medically-tailored refrigerated or frozen meals (5 lunches and 5 dinners) delivered to their home weekly. All meals are planned by a registered dietician. Meals have minimal preparation time, can be heated by stove, oven, or microwave, and will be provided free-of-charge. Because the meals are medically tailored, participants are asked not to share them. Adherence to meals and food sharing will be measured using food consumption diaries
Participants randomized to this intervention will be referred to their county WIC program through an already developed electronic referral process. To enable WIC offices to receive referrals and easily communicate with healthcare teams, our EHR also offers a community provider-facing, read-only EHR version. We have already successfully provided WIC staff with access and training for our ongoing WIC screening and referral pilot in pediatrics.
Participants will receive the same intervention as the electronic WIC referral. In addition, a patient care navigator will meet with the participant at enrollment to discuss any anticipated barriers to accessing WIC. The purpose of the visit is to build rapport and trust and to identify any social and structural barriers to enrolling in WIC. The navigator will also contact participants at 2 weeks to discuss any additional barriers reported and as necessary after the baseline visit. Specific counseling will be tailored based on individual's needs, for example difficulty with paperwork. The navigator will also assess any additional community resources to assist the participant with FI (e.g., local food pantries).
Time frame: Baseline
Proportion of eligible patients who enroll in the study based on study logs
Time frame: Month 6
The proportion of eligible participants who complete 3-month and 6-month follow-up data collection based on study log
Time frame: Month 3
The proportion of eligible participants who are re-randomized to a stage 2 intervention based on study log.
Time frame: Month 6
Survey participants using the validated 10-item USDA Adult FSSM, with a 30-day look back period. The tool measures food security over the prior 30 days. Using the standardized scoring provided by the USDA to assess participants responses. This produces a raw score that ranges from 0 to 10 with higher scores indicating worse FI.
High Food Security: Raw score of 0. Marginal Food Security: Raw score of 1-2. Low Food Security: Raw score of 3-5. Very Low Food Security: Raw score of 6-1
Time frame: Month 6
Differences in the incidence of gestational diabetes over time based on data extraction from the electronic health record.
Time frame: Post-delivery
We will determine the proportion of individuals with excess gestational weight gain. Will be determined by data extraction from the electronic health record and defined as the following: If pre-pregnancy BMI ≥30, gaining ≥20lbs; if BMI 25-29.9, gaining ≥25lbs; if BMI <25, gaining ≥35lbs.
Time frame: Post-delivery
Incident number of diagnoses at outpatient, emergency department or hospital encounter based on ICD-10 codes through data extraction from the electronic health record
Time frame: month 6
Change in the number of community resources used (e.g. food pantries, supplemental nutrition assistance program) based on self-report in the study survey.
Time frame: Baseline
Infant birth weight at the time of delivery based on data extraction from the electronic health record.
Time frame: Baseline
Infant gestational age at the time of delivery based on data extraction from the electronic health record
Time frame: Baseline
Number of Deliveries based on data extraction from the EHR.
Time frame: Baseline
Infant APGARS, Scores based on data extraction from the EHR. The Apgar score is a quick assessment of a newborn's health, evaluating five key areas: heart rate, respiratory effort, muscle tone, reflex irritability, and skin color. Each area is scored from 0 to 2, with a total score ranging from 0 to 10. A score of 7 or above is considered good, indicating the baby is in generally good health. Lower scores may indicate the need for medical assistance, but do not necessarily predict long-term health problems.
7-10: Normal, indicating good health and usually requiring only routine post-delivery care.
4-6: May require some assistance with breathing or other interventions. 0-3: Critical, requiring immediate and potentially life-saving medical attention.
Time frame: Baseline
breastfeeding status based on data extraction from the EHR
Time frame: Baseline and month 6
Episodes of hypo- or hyperglycemic episodes based on 14-days continuous glucose monitoring at baseline and 6 months.
Time frame: Month 6
Report of out-of-pocket monthly expenditures on food based on study survey
Time frame: Month 6
Change fruit and vegetable intake over time based on the National Cancer Institute's (NCI) Fruit and Vegetable screener. The NCI Fruit and Vegetable screener measure the frequency and usual portion size for 9 fruit and vegetable components over the prior month.
Time frame: Month 6
Change in depressive symptoms over time based on data extraction from the electronic health record. Depressive systems are collected at each OB visit using the validated Patient Health Questionnaire-2 (PHQ-2). Those with a positive PHQ-2 are reflexively assessed using the full PHQ-9. Scores range from 0-27 with higher scores representing a higher number of depressive systems.
Time frame: Month 6
Change in stress based on the Perceived Stress Scale as part of the study survey. Scores range from 0-40 with higher scores representing higher perceived stress.
Time frame: Baseline
Number of missed appointments, emergency department use, and hospitalizations based on data extraction from the EHR.
Contact information is provided by the study sponsor or research team.
Deepak Palakshappa, MD, MSHP
CONTACT
Rebecca Stone, MPH
CONTACT
Wake Forest University Health Sciences
Other
Feasibility of an ADAPTive Intervention to Improve Food Security and Maternal-Child Health (ADAPT-MCH)
Acronym: ADAPT-MCH
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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